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Joints

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A Deep Learning Approach for Human Action Recognition Using Skeletal Information.

Advances in experimental medicine and biology
In this paper we present an approach toward human action detection for activities of daily living (ADLs) that uses a convolutional neural network (CNN). The network is trained on discrete Fourier transform (DFT) images that result from raw sensor rea...

A practical 3D-printed soft robotic prosthetic hand with multi-articulating capabilities.

PloS one
Soft robotic hands with monolithic structure have shown great potential to be used as prostheses due to their advantages to yield light weight and compact designs as well as its ease of manufacture. However, existing soft prosthetic hands design were...

Weakly Supervised Adversarial Learning for 3D Human Pose Estimation from Point Clouds.

IEEE transactions on visualization and computer graphics
Point clouds-based 3D human pose estimation that aims to recover the 3D locations of human skeleton joints plays an important role in many AR/VR applications. The success of existing methods is generally built upon large scale data annotated with 3D ...

Multi-Person Pose Estimation Using an Orientation and Occlusion Aware Deep Learning Network.

Sensors (Basel, Switzerland)
Image based human behavior and activity understanding has been a hot topic in the field of computer vision and multimedia. As an important part, skeleton estimation, which is also called pose estimation, has attracted lots of interests. For pose esti...

An untethered isoperimetric soft robot.

Science robotics
For robots to be useful for real-world applications, they must be safe around humans, be adaptable to their environment, and operate in an untethered manner. Soft robots could potentially meet these requirements; however, existing soft robotic archit...

Real-Time Human Action Recognition with a Low-Cost RGB Camera and Mobile Robot Platform.

Sensors (Basel, Switzerland)
Human action recognition is an important research area in the field of computer vision that can be applied in surveillance, assisted living, and robotic systems interacting with people. Although various approaches have been widely used, recent studie...

GAS-GCN: Gated Action-Specific Graph Convolutional Networks for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland)
Skeleton-based action recognition has achieved great advances with the development of graph convolutional networks (GCNs). Many existing GCNs-based models only use the fixed hand-crafted adjacency matrix to describe the connections between human body...

Applying cascaded convolutional neural network design further enhances automatic scoring of arthritis disease activity on ultrasound images from rheumatoid arthritis patients.

Annals of the rheumatic diseases
OBJECTIVES: We have previously shown that neural network technology can be used for scoring arthritis disease activity in ultrasound images from rheumatoid arthritis (RA) patients, giving scores according to the EULAR-OMERACT grading system. We have ...

Neurodynamic modeling of the fruit fly Drosophila melanogaster.

Bioinspiration & biomimetics
This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers model...

HRDepthNet: Depth Image-Based Marker-Less Tracking of Body Joints.

Sensors (Basel, Switzerland)
With approaches for the detection of joint positions in color images such as HRNet and OpenPose being available, consideration of corresponding approaches for depth images is limited even though depth images have several advantages over color images ...